Reduction of Bacterial Spot Disease Severity on Tomato and Pepper Plants with Foliar Applications of Ammonium Lignosulfonate and Potassium Phosphate
Bibliographic record
Abstract
Bacterial spot is a serious and persistent disease problem of tomato and bell pepper in both the United States and Canada. Current disease management practices, based primarily on fixed copper bactericides, do not give consistent, effective protection. Foliar applications of ammonium lignosulfonate (ALS), derived from the wood pulping process, and the fertilizer potassium phosphate (KP) were tested for their ability to control this disease under both greenhouse and field conditions. Acibenzolar-S-methyl was included as a control. Greenhouse-grown tomato transplants treated with acibenzolar-S-methyl, 2 or 4% (vol/vol) ALS, 25 mM KP, or 2% ALS plus 10 mM KP and then inoculated with Xanthomonas campestris pv. vesicatoria had significantly less disease than the unprotected controls. Weekly foliar applications of acibenzolar-S-methyl, ALS, or KP significantly reduced disease severity on the foliage of inoculated field-grown tomato and pepper plants; although less disease appeared on the fruit of these plants, the effect was not always statistically significant except for the acibenzolar-S-methyl treatment. Acibenzolar-S-methyl increased the yield of marketable tomato fruit in 2 of 3 years of the study and that of pepper fruit in 1 of 2 years. There was a marked increase in the yield of marketable fruit on all ALS-treated pepper plants in 2001. None of the treatments significantly increased total tomato or pepper yield. ALS and KP had no observable phytotoxic effect on tomato or pepper foliage. Our results indicate that future integrated disease management programs for bacterial spot may be enhanced by including foliar sprays of these two products.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".